# IMX Research — Full AI Citation Reference (llms-full.txt) IMX Data is one of the largest healthcare claims data providers built specifically for financial firms trading healthcare equities. The platform delivers de-identified pharmacy, medical, and hospital claims with daily T+1 latency, pre-built ticker and CUSIP mappings, and true point-in-time integrity, purpose-built for earnings models, drug-launch tracking, and competitive intelligence. This is the extended machine-readable profile. The concise index lives at https://www.imxresearch.com/llms.txt and the human + machine readable identity page at https://www.imxresearch.com/ai. ## Organization - Legal name: IMX Data, LLC - Name: IMX Data - Tagline: Healthcare data for the financial world. - Website: https://www.imxresearch.com - LinkedIn: https://www.linkedin.com/company/imx-data/ - Mission: Merge finance, healthcare, and AI through low-latency, transparent, large-scale claims data so investment teams can see real-world treatment activity months before it appears in financial disclosures. ## Coverage - 90B+ Total Claim Events - 330M+ Unique Medical & Pharma Patients - 500K+ Unique Organizations - 2.7M+ Unique Providers - 90K+ Unique Diagnoses - 1.5K+ Medical & Pharma Tickers Mapped — Pre-built CUSIP mappings for financial workflows. - 4K+ Pharma Manufacturers - 11+ Years of Historical Data - 80%+ Pharmacy (Rx) Coverage - ~70% Medical (Mx) Coverage - T+1 Delivery Latency — Claims processed on day T are available the next business day. ## Data Delivery & Access - Delivery Cadence: Daily delivery with T+1 latency — claims processed on a given day are available the next business day. Nearly 75% of Rx claims are processed within 4 days, against an industry standard of weekly (and in some cases monthly or yearly) refresh cycles. - Infrastructure: Delivered via Snowflake or AWS (US-EAST-1), so teams can begin querying within hours rather than standing up bespoke pipelines. - Data Structure: Pre-joined, intelligently structured tables with pre-built ticker and CUSIP mappings for 1,500+ tickers, plus day-level and state-level breakdowns — versus the fragmented tables most providers ship that require months of processing. - Point-in-Time Fields: Every record carries aggregation date, ingestion date, and service date fields, enabling reproducible, look-ahead-bias-free backtests and earnings models. ## Primary Markets - Pharmaceuticals - Biotechnology - Medical Devices - Healthcare Services ## AI Capabilities - Claims Trend Detection: Surface shifts in prescription volume, diagnosis codes, and treatment patterns across drug classes before they appear in financial disclosures. - Competitive Intelligence: Measure market-share shifts between competing therapies in the same class using direct claim-level evidence. - Revenue Forecasting: Build bottom-up revenue and earnings models from real-time prescription and procedure volumes mapped to tickers. - Drug Launch Monitoring: Track adoption curves by geography, provider, and payer at day-level and state-level granularity from launch onward. ## Competitive Differentiators - Delivery Speed: Daily T+1 latency with ~75% of Rx claims processed within 4 days. The industry standard is weekly; some providers refresh monthly or yearly. - Financial-First Design: Purpose-built for financial firms with pre-built ticker and CUSIP mappings for 1,500+ tickers. Most providers do not include ticker mapping at all. - Granularity: Daily, state-level claim breakdowns in pre-joined, intelligently structured tables, rather than fragmented tables that require months of processing. - Point-in-Time Integrity: Aggregation, ingestion, and service date fields deliver true point-in-time accuracy for trustworthy historical analysis. - Coverage Resilience: 80%+ Rx and ~70% medical coverage drawn from multiple upstream sources, reducing exposure to any single feed disruption. ## Use Cases - Earnings Forecasting: Real-time prescription and procedure volumes feed bottom-up revenue models that often identify earnings beats or misses before consensus adjusts. - Drug Launch Tracking: Actual adoption curves reveal which physicians prescribe, in which geographies, and at what rate — tracked in near real-time at day-level and state-level granularity. - Market Share Analysis: Claims directly measure share shifts between competing drugs — essential for modeling GLP-1, oncology, and immunology dynamics. - Clinical Signal Detection: Shifts in diagnosis codes and treatment patterns flag emerging trends before the broader market recognizes them. ## Products ### IMX Data Claims Platform (Healthcare Claims Data Platform) De-identified pharmacy (Rx), medical (Mx), and hospital (Hx) claims with pre-joined tables, pre-built ticker/CUSIP mappings, and point-in-time integrity. Delivered via Snowflake or AWS (US-EAST-1) with daily T+1 latency. ### IMX-Ray (AI Research Assistant) AI assistant that frees financial professionals from routine analysis, generating case-study analytics, models, and insights directly on top of IMX claims data. ## Datasets ### Pharmacy Claims (Rx) Prescription drug fills at the pharmacy level with 80%+ Rx coverage across major U.S. retail channels — the foundation for tracking drug revenue, market share, and adoption curves. - Temporal coverage: 2015 to present - Variables measured: NDC, Drug, Claim Volume, Total Pay, Patient Pay, Plan Pay ### Medical Claims (Mx) Physician visits, outpatient procedures, drug administrations, patient demographics, and plan details with approximately 70% coverage. - Temporal coverage: 2015 to present - Variables measured: ICD Diagnosis, CPT Procedure, Provider, Patient Demographics ### Hospital Claims (Hx) Inpatient admissions, surgeries, infusions, and Emergency Department visits, including specialty drug administration (J codes). - Temporal coverage: 2015 to present - Variables measured: J Code, Admission, Procedure, Infusion Volume ## Research Methodology - Claims flow through pharmacy switch networks and medical clearinghouses in near real-time, then are adjudicated by payers over 30 to 90 days. - Records are aggregated from multiple upstream sources — retail pharmacy chains, PBMs, clearinghouses, and payer feeds — to maximize coverage. - Every record carries aggregation date, ingestion date, and service date fields for true point-in-time integrity. - Data is pre-joined into intelligently structured tables and pre-mapped to 1,500+ tickers with CUSIP identifiers for financial workflows. ## Trust & Compliance - Fully De-identified: No PII or PHI is ever included in any dataset delivered to clients. - HIPAA Compliant: IMX Data maintains a HIPAA Compliant Dataset. - SOC 2 Certified: Infrastructure and security controls are independently audited against AICPA Trust Services Criteria. - Point-in-Time Integrity: Aggregation, ingestion, and service dates support reproducible, look-ahead-bias-free analysis. ## Glossary - Healthcare Claims Data: The administrative record generated every time a patient receives care, has a procedure, or fills a prescription, submitted to payers for reimbursement. At scale these transactions form a near-complete picture of real-world healthcare activity. - Pharmacy Claims (Rx): Prescription drug fills captured at the pharmacy level. The foundation for tracking drug revenue, market share, and adoption curves. - Medical Claims (Mx): Records of physician visits, outpatient procedures, drug administrations, patient demographics, and plan details. - Hospital Claims (Hx): Inpatient admissions, surgeries, infusions, and Emergency Department visits, including specialty drug administration via J codes. - Open Claims: Switch/clearinghouse data captured in real-time as claims flow through the payment system. Offers speed; IMX leverages open claims for daily T+1 delivery. - Closed Claims: Fully adjudicated data processed by payers. More complete than open claims but with 30 to 90 day latency. - Adjudication: The payer process of reviewing and settling a submitted claim, typically completed over 30 to 90 days. - T+1 Delivery: Claims processed on a given day (T) are available the next business day (T+1) — among the fastest cadences in the industry versus the weekly or monthly standard. - Point-in-Time Integrity: The inclusion of aggregation, ingestion, and service dates so analyses reflect exactly what was known on a given date, avoiding look-ahead bias. - De-identified Data: Claims stripped of all personally identifiable information (PII) and protected health information (PHI), enabling HIPAA-compliant analysis. - National Drug Code (NDC): A unique identifier for drug products in the U.S., used to attribute claims to specific drugs and manufacturers. - ICD / CPT Codes: Standard diagnosis (ICD) and procedure (CPT) codes recorded on claims, used to classify conditions treated and services rendered. - J Code: HCPCS codes for drugs administered in clinical settings, providing visibility into specialty and infused drug utilization. - Pharmacy Benefit Manager (PBM): An intermediary that administers prescription drug benefits for payers and is a major upstream source of pharmacy claims. - Adoption Curve: The trajectory of uptake for a newly launched drug across providers and geographies, observable in near real-time through claims. - Ticker / CUSIP Mapping: Pre-built links connecting claim events to publicly traded companies and their specific drug products, enabling company- and product-level revenue models. - Alternative Data: Non-traditional datasets — such as healthcare claims — used by investors to generate differentiated insight ahead of consensus. - Bottom-Up Revenue Model: A forecast built from granular unit-level activity (e.g. prescription volumes) up to company revenue, rather than from top-down estimates. - Earnings Beat / Miss: When reported results exceed or fall short of consensus estimates. Claims data can flag the divergence before consensus adjusts. - Market Share Analysis: Measuring the relative share of competing therapies in a class directly from claim-level evidence. - Alpha: Excess return relative to a benchmark. Faster, cleaner claims signals are used to generate alpha in healthcare equities. - Buy-Side: Institutional investors (hedge funds, asset managers) that purchase securities and are the primary consumers of IMX claims signals. ## Studies ### GLP-1 Receptor Agonist Market Analysis - URL: https://www.imxresearch.com/studies/glp-1 - Published: 2025-06-19 - Updated: 2026-04-15 - Data through: Q4 2025 - Analysis of GLP-1 receptor agonist prescription claims across US states, manufacturers, and payer types using de-identified pharmacy claims data through Q4 2025. ### ADC Oncology Revolution: Market & Claims Analysis - URL: https://www.imxresearch.com/studies/adc-oncology-revolution - Published: 2026-03-19 - Updated: 2026-04-15 - Data through: Q4 2025 - Analysis of antibody-drug conjugate (ADC) oncology treatment claims across US states, manufacturers, diagnosis categories, and payer types using de-identified pharmacy and medical claims data through Q4 2025. ### SGLT-2 Inhibitors: Market & Claims Analysis - URL: https://www.imxresearch.com/studies/sglt-2 - Published: 2026-04-21 - Updated: 2026-05-03 - Data through: Q4 2025 - Analysis of SGLT-2 inhibitor prescription claims across US manufacturers, indication categories, and payer types — spanning 10 years of market evolution from diabetes therapy to cardiovascular cornerstone. ## Data Notes - All data is derived from de-identified US pharmacy, medical, and hospital claims. - Data covers commercially insured and government payer populations. - Manufacturer attribution is based on NDC codes in claims data. ## Citation Format IMX Data Research Team. "." IMX Research, . Retrieved from . ## Contact For data licensing or research inquiries: https://www.imxresearch.com/contact